Abstract: The development of the United Arab Emirates (UAE)
into a regional trade, tourism, finance and logistics hub has
transformed its real estate markets. However, speculative activity and
price volatility remain concerns. UAE residential market values
(MV) are exposed to fluctuations in capital flows and migration
which, in turn, are affected by geopolitical uncertainty, oil price
volatility and global investment market sentiment. Internally, a
complex interplay between administrative boundaries, land tenure,
building quality and evolving location characteristics fragments UAE
residential property markets. In short, the UAE Residential Valuation
System (UAE-RVS) confronts multiple challenges to collect, filter
and analyze relevant information in complex and dynamic spatial and
capital markets. A robust (RVS) can mitigate the risk of unhelpful
volatility, speculative excess or investment mistakes. The research
outlines the institutional, ontological, dynamic and epistemological
issues at play. We highlight the importance of system capabilities,
valuation standard salience and stakeholders trust.
Abstract: To date, one of the few comprehensive indicators for
the measurement of food security is the Global Food Security Index
(GFSI). This index is a dynamic quantitative and qualitative
benchmarking model, constructed from 28 unique indicators, that
measures drivers of food security across both developing and
developed countries. Whereas the GFSI has been calculated across a
set of 109 countries, in this paper we aim to present and compare, for
the Middle East and North Africa (MENA), 1) the Food Security
Index scores achieved and 2) the data available on affordability,
availability, and quality of food. The data for this work was taken
from the latest available report published by the creators of the GFSI,
which in turn used information from national and international
statistical sources. MENA countries rank from place 17/109 (Israel,
although with resent political turmoil this is likely to have changed)
to place 91/109 (Yemen) with household expenditure spent in food
ranging from 15.5% (Israel) to 60% (Egypt). Lower spending on food
as a share of household consumption in most countries and better
food safety net programs in the MENA have contributed to a notable
increase in food affordability. The region has also, however,
experienced a decline in food availability, owing to more limited
food supplies and higher volatility of agricultural production. In
terms of food quality and safety the MENA has the top ranking
country (Israel). The most frequent challenges faced by the countries
of the MENA include public expenditure on agricultural research and
development as well as volatility of agricultural production. Food
security is a complex phenomenon that interacts with many other
indicators of a country’s wellbeing; in the MENA it is slowly but
markedly improving.
Abstract: The financial crises caused a collapse in prices of
most asset classes, raising the attention on alternative investments
such as sukuk, a smaller, fast growing but often misunderstood
market. We study diversification benefits of sukuk, their correlation
with other asset classes and the effects of their inclusion in
investment portfolios of institutional and retail investors, through a
comprehensive comparison of their risk/return profiles during and
after the financial crisis.
We find a beneficial performance adjusted for the specific
volatility together with a lower correlation especially during the
financial crisis. The distribution of sukuk returns is positively skewed
and leptokurtic, with a risk/return profile similarly to high yield
bonds. Overall, our results suggest that sukuk present diversification
opportunities, a significant volatility-adjusted performance and lower
correlations especially during the financial crisis.
Our findings are relevant for a number of institutional investors.
Long term investors, such as life insurers would benefit from sukuk’s
protective features during financial crisis yet keeping return and
growth opportunities, whereas banks would gain due to their role of
placers, advisors, market makers or underwriters.
Abstract: In this paper it was examined the influence of margin
regulation on stock market volatility in EU 1993 – 2014. Regulating
margin requirements or haircuts for securities financing transactions
has for a long time been considered as a potential tool to limit the
build-up of leverage and dampen volatility in financial markets. The
margin requirement dictates how much investors can borrow against
these securities. Margin can be an important part of investment.
Using daily and monthly stock returns and there is no convincing
evidence that EU Regulation margin requirements have served to
dampen stock market volatility. In this paper was detected the
expected negative relation between margin requirements and the
amount of margin credit outstanding. Also, it confirmed that changes
in margin requirements by the EU regulation have tended to follow
than lead changes in market volatility. For the analysis have been
used the modified Levene statistics to test whether the standard
deviation of stock returns in the 25, 50 and 100 days preceding
margin changes is the same as that in the succeeding 25, 50 and 100
days. The analysis started in May 1993 when it was first empowered
to set the initial margin requirement and the last sample was in May
2014. To test whether margin requirements influence stock market
volatility over the long term, the sample of stock returns was divided
into 14 periods, according to the 14 changes in margin requirements.
Abstract: Various biomass based resources, which can be used
as an extender, or a complete substitute of diesel fuel may have very
significant role in the development of agriculture, industrial and
transport sectors in the energy crisis. Use of Karanja oil methyl ester
biodiesel in a CI DI engine was found highly compatible with engine
performance along with lower exhaust emission as compared to
diesel fuel but with slightly higher NOx emission and low wear
characteristics. The combustion related properties of vegetable oils
are somewhat similar to diesel oil. Neat vegetable oils or their blends
with diesel, however, pose various long-term problems in
compression ignition engines. These undesirable features of
vegetable oils are because of their inherent properties like high
viscosity, low volatility, and polyunsaturated character. Pongamia
methyl ester (PME) was prepared by transesterification process using
methanol for long term engine operations. The physical and
combustion-related properties of the fuels thus developed were found
to be closer to that of the diesel. A neat biodiesel (PME) was selected
as a fuel for the tribological study of biofuels.
Two similar new engines were completely disassembled and
subjected to dimensioning of various vital moving parts and then
subjected to long-term endurance tests on neat biodiesel and diesel
respectively. After completion of the test, both the engines were
again disassembled for physical inspection and wear measurement of
various vital parts. The lubricating oil samples drawn from both
engines were subjected to atomic absorption spectroscopy (AAS) for
measurement of various wear metal traces present. The additional
lubricating property of biodiesel fuel due to higher viscosity as
compared to diesel fuel resulted in lower wear of moving parts and
thus improved the engine durability with a bio-diesel fuel. Results
reported from AAS tests confirmed substantially lower wear and thus
improved life for biodiesel operated engines.
Abstract: In this paper, we consider the application of Extreme
Value Theory as a risk measurement tool. The Value at Risk, for a set
of indices, from six Stock Exchanges of Frontier markets is
calculated using the Peaks over Threshold method and the
performance of the model index-wise is evaluated using coverage
tests and loss functions. Our results show that “fattailedness” alone of
the data is not enough to justify the use of EVT as a VaR approach.
The structure of the returns dynamics is also a determining factor.
This approach works fine in markets which have had extremes
occurring in the past thus making the model capable of coping with
extremes coming up (Colombo, Tunisia and Zagreb Stock
Exchanges). On the other hand, we find that indices with lower past
than present volatility fail to adequately deal with future extremes
(Mauritius and Kazakhstan). We also conclude that using EVT alone
produces quite static VaR figures not reflecting the actual dynamics
of the data.
Abstract: In this paper, we forecast the volatility of Baht/USDs using Markov Regime Switching GARCH (MRS-GARCH) models. These models allow volatility to have different dynamics according to unobserved regime variables. The main purpose of this paper is to find out whether MRS-GARCH models are an improvement on the GARCH type models in terms of modeling and forecasting Baht/USD volatility. The MRS-GARCH is the best performance model for Baht/USD volatility in short term but the GARCH model is best perform for long term.
Abstract: Based on the fact that volatility is time varying in high frequency data and that periods of high volatility tend to cluster, the most successful and popular models in modeling time varying volatility are GARCH type models. When financial returns exhibit sudden jumps that are due to structural breaks, standard GARCH models show high volatility persistence, i.e. integrated behavior of the conditional variance. In such situations models in which the parameters are allowed to change over time are more appropriate. This paper compares different GARCH models in terms of their ability to describe structural changes in returns caused by financial crisis at stock markets of six selected central and east European countries. The empirical analysis demonstrates that Markov regime switching GARCH model resolves the problem of excessive persistence and outperforms uni-regime GARCH models in forecasting volatility when sudden switching occurs in response to financial crisis.
Abstract: The goal of this study was to increase the awareness of the description and assessments of rice acreage response and to offer mechanisms for agricultural policy scrutiny. The ordinary least square (OLS) technique was utilized to determine the coefficients of acreage response models for the rice varieties. The magnitudes of the coefficients (λ) of both the ROK lagged and NERICA lagged acreages were found positive and highly significant, which indicates that farmers’ adjustment rate was very low. Regarding lagged actual price for both the ROK and NERICE rice varieties, the short-run price elasticitieswere lower than long-run, which is suggesting a long term adjustment of the acreage under the crop.
However, the apparent recommendations for policy transformation are to open farm gate prices and to decrease government’s involvement in agricultural sector especially in the acquisition of agricultural inputs. Impending research have to be centered on how this might be better realized. Necessary conditions should be made available to the private sector by means of minimizing price volatility. In accordance with structural reforms, it is necessary to convey output prices to farmers with minimum distortion. There is need to eradicate price subsidies and control, which generate distortion in the market in addition to huge financial costs.
Abstract: In the past decades, the environment of production companies showed a permanent increase in dynamic and volatility in the form of demand fluctuations, new technologies or global crises. As a reaction to these new requirements, changeability of production systems came into attention. A changeable production system can adapt to these changes quickly and with little effort. Even though demand for changeable production exists for some time, the practical application is still insufficient.
To overcome this deficit, a three year research project at the Department of Production Systems and Logistics at the Leibniz University of Hanover/ Germany was initiated. As a result of this project, different concepts have been developed to design production changeable. An excerpt of the results will be presented in this paper. An eight step procedure will be presented to design the changeability of production logistics. This procedure has been applied at a German manufacturer of high demanding weighing machines. The developed procedure, their application in industry, as well as the major results of the application will be presented.
Abstract: In order to ensure a high service level industrial enterprises have to maintain safety-stock that directly influences the economic efficiency at the same time. This paper analyses established mathematical methods to calculate safety-stock. Therefore, the performance measured in stock and service level is appraised and the limits of several methods are depicted. Afterwards, a new dynamic approach is presented to gain an extensive method to calculate safety-stock that also takes the knowledge of future volatility into account.
Abstract: German electricity European options on futures using
Lévy processes for the underlying asset are examined. Implied
volatility evolution, under each of the considered models, is
discussed after calibrating for the Merton jump diffusion (MJD),
variance gamma (VG), normal inverse Gaussian (NIG), Carr, Geman,
Madan and Yor (CGMY) and the Black and Scholes (B&S) model.
Implied volatility is examined for the entire sample period, revealing
some curious features about market evolution, where data fitting
performances of the five models are compared. It is shown that
variance gamma processes provide relatively better results and that
implied volatility shows significant differences through time, having
increasingly evolved. Volatility changes for changed uncertainty, or
else, increasing futures prices and there is evidence for the need to
account for seasonality when modelling both electricity spot/futures
prices and volatility.
Abstract: The New Basel Capital Accord (Basel II) influences how financial institutions around the world, and especially European Union institutions, determine the amount of capital to reserve. However, as the recent global crisis has shown, the revision of Basel II is needed to reflect current trends, such as increased volatility and correlation, in the world financial markets. The overall objective of Basel II is to increase the safety and soundness of the international financial system. Basel II builds on three main pillars: Pillar I deals with the minimum capital requirements for credit, market and operational risk, Pillar II focuses on the supervisory review process and finally Pillar III promotes market discipline through enhanced disclosure requirements for banks. The aim of this paper is to provide the historical background, key features and impact of Basel II on financial markets. Moreover, we discuss new proposals for international bank regulation (sometimes referred to as Basel III) which include requirements for higher quality, constituency and transparency of banks' capital and risk management, regulation of OTC markets and introduction of new liquidity standards for internationally active banks.
Abstract: The basic objective of this paper is to measure and
compare the profitability of investments made by the small and
marginal farmers of the state of West Bengal in floriculture shifting
from the traditional cultivation of paddy. A comparison of IRR is
made to establish the fact that cultivation of flowers yield higher
returns farmers whose land size is so small that viability of paddy
cultivation is raising a question mark. A detailed study of the price
behavior of the flower crop has been carried out in which the factors
leading to the volatility of the price and the dispersion of the range
have also been discussed. Finally the incremental incomes of the
farmers have been calculated with the help of imputed income from
paddy cultivation and the reported income from the selected flowers.
The study shows that the farmers stand gainers if they opt for flower
cultivation.
Abstract: By systematically applying different engineering
methods, difficult financial problems become approachable. Using a
combination of theory and techniques such as wavelet transform,
time series data mining, Markov chain based discrete stochastic
optimization, and evolutionary algorithms, this work formulated a
strategy to characterize and forecast non-linear time series. It
attempted to extract typical features from the volatility data sets of
S&P100 and S&P500 indices that include abrupt drops, jumps and
other non-linearity. As a result, accuracy of forecasting has reached
an average of over 75% surpassing any other publicly available
results on the forecast of any financial index.
Abstract: The paper evaluates several hundred one-day-ahead
VaR forecasting models in the time period between the years 2004
and 2009 on data from six world stock indices - DJI, GSPC, IXIC,
FTSE, GDAXI and N225. The models model mean using the ARMA
processes with up to two lags and variance with one of GARCH,
EGARCH or TARCH processes with up to two lags. The models are
estimated on the data from the in-sample period and their forecasting
accuracy is evaluated on the out-of-sample data, which are more
volatile. The main aim of the paper is to test whether a model
estimated on data with lower volatility can be used in periods with
higher volatility. The evaluation is based on the conditional coverage
test and is performed on each stock index separately. The primary
result of the paper is that the volatility is best modelled using a
GARCH process and that an ARMA process pattern cannot be found
in analyzed time series.
Abstract: The purpose of this paper is to investigate the
influence of a number of variables on the conditional mean and
conditional variance of credit spread changes. The empirical analysis
in this paper is conducted within the context of bivariate GARCH-in-
Mean models, using the so-called BEKK parameterization. We show
that credit spread changes are determined by interest-rate and equityreturn
variables, which is in line with theory as provided by the
structural models of default. We also identify the credit spread
change volatility as an important determinant of credit spread
changes, and provide evidence on the transmission of volatility
between the variables under study.
Abstract: This paper deals with heterogeneous autoregressive
models of realized volatility (HAR-RV models) on high-frequency
data of stock indices in the USA. Its aim is to capture the behavior of
three groups of market participants trading on a daily, weekly and
monthly basis and assess their role in predicting the daily realized
volatility. The benefits of this work lies mainly in the application of
heterogeneous autoregressive models of realized volatility on stock
indices in the USA with a special aim to analyze an impact of the
global financial crisis on applied models forecasting performance.
We use three data sets, the first one from the period before the global
financial crisis occurred in the years 2006-2007, the second one from
the period when the global financial crisis fully hit the U.S. financial
market in 2008-2009 years, and the last period was defined over
2010-2011 years. The model output indicates that estimated realized
volatility in the market is very much determined by daily traders and
in some cases excludes the impact of those market participants who
trade on monthly basis.
Abstract: This paper deals with the problem of thermal and
mechanical shocks, which rising during operation, mostly at
interrupted cut. Here will be solved their impact on the cutting edge
tool life, the impact of coating technology on resistance to shocks
and experimental determination of tool life in heating flame.
Resistance of removable cutting edges against thermal and
mechanical shock is an important indicator of quality as well as its
abrasion resistance. Breach of the edge or its crumble may occur due
to cyclic loading. We can observe it not only during the interrupted
cutting (milling, turning areas abandoned hole or slot), but also in
continuous cutting. This is due to the volatility of cutting force on
cutting. Frequency of the volatility in this case depends on the type
of rising chips (chip size element). For difficult-to-machine materials
such as austenitic steel particularly happened at higher cutting speeds
for the localization of plastic deformation in the shear plane and for
the inception of separate elements substantially continuous chips.
This leads to variations of cutting forces substantially greater than for
other types of steel.
Abstract: It has become crucial over the years for nations to
improve their credit scoring methods and techniques in light of the
increasing volatility of the global economy. Statistical methods or
tools have been the favoured means for this; however artificial
intelligence or soft computing based techniques are becoming
increasingly preferred due to their proficient and precise nature and
relative simplicity. This work presents a comparison between Support
Vector Machines and Artificial Neural Networks two popular soft
computing models when applied to credit scoring. Amidst the
different criteria-s that can be used for comparisons; accuracy,
computational complexity and processing times are the selected
criteria used to evaluate both models. Furthermore the German credit
scoring dataset which is a real world dataset is used to train and test
both developed models. Experimental results obtained from our study
suggest that although both soft computing models could be used with
a high degree of accuracy, Artificial Neural Networks deliver better
results than Support Vector Machines.